THE ANALYTICS EDGE IN HEALTHCARE
Dynamic Ideas

The Analytics Edge In Healthcare

Dimitris Bertsimas | Agni Orfanoudaki | Holly Wiberg

A practical introduction to how machine learning and optimization transform clinical and operational decisions — from technical foundations to integrated case studies across medical specialties.

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Front cover of The Analytics Edge in Healthcare by Dimitris Bertsimas, Agni Orfanoudaki, and Holly Wiberg
About the book

From data and models to better decisions

Analytics is transforming healthcare operations, empowering medical professionals and administrators to leverage data and models to make better decisions. The Analytics Edge in Healthcare provides a practical introduction to the field.

The book pursues three goals: to show healthcare professionals the edge that analytics can bring to their daily practice, to provide a broad yet concise overview of the technical foundations of the field, and to highlight recent advances — from interpretable risk scores to fair allocation policies — through real applications developed with leading medical centers.

Analytics is not in conflict with medical expertise, but synergistic with it: a new paradigm of evidence-based care, learned from the records of millions of patients.

Medical students Doctors & nurses Hospital executives & administrators Analytics students & researchers
The book's objectives
  1. I

    Clinical practice

    Demonstrate the edge of data-driven models to healthcare professionals in their everyday clinical decisions.

  2. II

    Methodological foundations

    Provide a broad yet rigorous overview of the technical foundations underpinning the field.

  3. III

    Contemporary advances

    Examine recent developments through applications developed with leading medical centers.

Inside the book

Methods, case studies & summary tables

Twenty-two chapters in three parts: a complete methods toolkit, nine integrated case studies spanning clinical specialties, and quick-reference summary tables of every method and evaluation metric.

Part I — Methods

The technical foundations

Each chapter introduces a class of algorithms through the lens of a real clinical example.

Supervised learning
  • 1Binary Classification · cancer mortality risk
  • 2Regression · childhood asthma & allergies
  • 3Survival Analysis · coronary artery disease
Unsupervised learning
  • 4Clustering · Framingham Heart Study
  • 5Missing Data Imputation · stroke risk score
Deep learning
  • 6Neural Networks · sarcoma detection
  • 7Natural Language Processing · neurology ICU
  • 8Multimodal Data · ICU outcomes
Learning for decision-making
  • 9Optimization · radiologist scheduling
  • 10Prescriptive Methods · personalized diabetes care
  • 11Fairness in Algorithms · transplantation policy
Part II — Integrated Case Studies

Analytics in practice

End-to-end applications combining techniques across medicine, operations, and policy.

  • 12Mortality & Morbidity in Emergency Surgery
  • 13Predicting Length of Stay with Interpretable Analytics
  • 14Hospital-Wide Inpatient Flow Optimization
  • 15Real-Time Heart Disease Prediction
  • 16Personalized Treatments for Coronary Artery Disease
  • 17Optimizing Chemotherapy Regimen Design
  • 18Reshaping Organ Allocation Policy
  • 19Alleviating Bias in Trauma Patient Management
  • 20A Data-Driven Response to COVID-19
Part III — Summary Tables.

Metrics and methods review

  • 21Methods Summary
  • 22Evaluation Metrics Summary
22
Chapters
3
Parts
9
Case studies
11
Classes of methods
978-1-7337885-4-0
ISBN

The authors

Dimitris Bertsimas

Massachusetts Institute of Technology

Boeing Professor of Operations Research, Associate Dean of Business Analytics, and faculty director of the Master of Business Analytics at MIT.

Agni Orfanoudaki

University of Oxford

Associate Professor of Operations Management at Saïd Business School and Fellow in Management Studies at Exeter College.

Holly Wiberg

Carnegie Mellon University

Assistant Professor of Operations Research and Public Policy at the Heinz College of Information Systems and Public Policy.

For students & educators

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